A problem which frequently occurs in the steering of motor vehicles is the difficulty in noticing obstacles in proximity to the motor vehicle which are located in a position not easily seen by the driver. A position such as this is conventionally known as the blind spot. A blind spot of this type is located, for example, in a direction of 90° to 170° from the direction of travel, both to the left and to the right of the motor vehicle. It is important for the driver of a motor vehicle to be alerted to the presence of obstacles in the blind spot, particularly when turning or changing lanes in a multi-lane road or highway.
Specially configured rear view mirrors or video cameras have been used to address this problem. These options do not provide adequate safety for the most part, as they must be visually evaluated by the driver, and in addition, in the case of the video camera, use relative complex technology.
It is also known to equip motor vehicles with radar systems which detect the presence of an obstacle in the blind spot of a vehicle and automatically produce a signal which alerts the driver of the vehicle to the presence of the obstacle.
Systems of this type must determine the relative velocity between the vehicle in which they are fitted and the potential obstacle in order to distinguish the obstacle from stationary objects. The commonly used terms, “host” and “target” will be used hereinafter for the vehicle equipped with the measuring system and the obstacle to be detected respectively.
A problem exists in that the absolute difference in velocity between two systems has to be estimated. Moreover, this type of problem is also significant in other areas of application, such as in aeronautical or rail engineering.
Considering the situation shown in FIG. 1, in which a system a and a system b travel with respective velocities Va and Vb, the simplest way of determining a differential velocity ΔV=Vb−Va is to observe the relative trajectory, also known as the object track, as a function of time. The temporal derivative of this trajectory thus directly represents the differential velocity.
This approach is efficient if a sensor system which can constantly detect a single representative reference point from the target is available. In conventional known sensor systems this generally involves what is known as a radar (radio detection and ranging) system. In these cases, a sensor system based on what is known as Doppler radar is frequently used. As is generally known, this involves transmitting a radar pulse to the target at a particular point in time T1 and detecting the backscattered pulse. A further pulse is transmitted at a later time T2 and the backscattered pulse is again detected.
The radial velocity between the host and the target leads to a phase shift between the two backscattered signals according to the known Doppler effect. The phase shift, the wavelength of the transmitted signal, and the time interval between the two measurements allow the velocity of the target to be calculated in the direction of observation. Velocity components normal to the direction of observation cannot be detected in this way.
Depending on the respective scenario and the resolution of the particular radar system, a representative reference point of the target can not always be observed in order to determine its trajectory. The further an object extends and the more extended its scatter surface is, the harder it is to determine object tracks and velocity therefrom.
In order to alleviate these difficulties, observation merging, a radar signal processing technique which merges a large number of observations has been utilized. If the perspective to the individual measurement points of the system to be observed, known as the object cluster, changes only marginally over time, a satisfactory level of accuracy can be achieved using this method. However, if the perspective changes significantly over time, which is certainly the case for parallel moving objects with considerable relative velocity, this type of evaluation cannot be used.
In addition, in many applications the targets are so extensive that a very widely scattered response signal reaches the radar receiver, with the additional problem that the phase centroids can be regarded as being almost randomly distributed from measurement cycle to measurement cycle. Thus, under such marginal conditions, the conventional evaluation process involving detection, corresponding classification and tracking does not fulfill its purpose.